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Task 2295 (Supervised Regression) cholesterol Uploaded 14-11-2019 by Christian Geißler
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estima tor=sklearn.linear_model.stochastic_gradient.SGDRegressor)(1)	Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicator	false
sklearn.impute._base.SimpleImputer(1)_copy	true
sklearn.impute._base.SimpleImputer(1)_fill_value	null
sklearn.impute._base.SimpleImputer(1)_missing_values	NaN
sklearn.impute._base.SimpleImputer(1)_strategy	"mean"
sklearn.impute._base.SimpleImputer(1)_verbose	0
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.linear_model.stochastic_gradient.SGDRegressor)(1)_memory	null
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.linear_model.stochastic_gradient.SGDRegressor)(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.linear_model.stochastic_gradient.SGDRegressor)(1)_verbose	false
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_alpha	0.01
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_average	false
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_early_stopping	true
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_epsilon	0.1
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_eta0	0.01035052217754343
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_fit_intercept	true
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_l1_ratio	0.191172186980897
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_learning_rate	"invscaling"
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_loss	"squared_loss"
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_max_iter	5444.294711468126
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_n_iter_no_change	5
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_penalty	"l2"
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_power_t	0.8
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_random_state	43679
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_shuffle	true
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_tol	8.518844126525303e-05
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_validation_fraction	0.1
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_verbose	0
sklearn.linear_model.stochastic_gradient.SGDRegressor(1)_warm_start	false